UNICITY: A depth maps database for people detection in security airlocks

UNICITY: A depth maps database for people detection in security airlocks.

UNICITY consists of 58k images collected from 65 recorded sequences with one or two people performing different behaviors including attacks and trickeries, like for instance tailgating (when a person walks very close to another to get into a restricted area). It also provides full annotation of people such as the location of head and shoulders. As as result, UNICITY is perfectly suited for training and adapting machine learning algorithms for video surveillance applications.

Main Features:

UNICITY consists of 58k images using two depth sensors.

65 recorded sequences with one or two people performing different behaviors such as attacks and tailgating.

UNICITY also provides code for evaluation and visualization, and full annotation of people such as the location of head and shoulders.

This new dataset is perfectly suited for training and adapting machine learning algorithms for video surveillance applications.

Citation:

Please cite the following paper if you use the UNICITY dataset in your work (papers, articles, reports, books, software, etc):